Sectional Dimensions Identification of Metal Profile by Image Processing

I. M. Orak, Şaban Şeker
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Abstract

In steel plants, estimation of the production system characteristic is highly critical to adjust the system parameters for best efficiency. Although the sys-tem parameters may be tuned very well, due to the machine and human factors involved in the production line some deficiencies may occur in product. It is important to detect such problems as early as possible. Surface defects and dimensional deviations are the most important quality problems. In this study, it is aimed to develop an approach to measure the dimensions of metal profiles by obtaining images of them. This will be of use in detecting the deviations in dimensions. A platform was introduced to simulate the real-time environment and images were taken from the metal profile using 4 laser light sources. The shape of the material is generated by combining the images taken from different cameras. Real dimensions were obtained by using image processing and mathematical conversion operations on the images. The re-sults obtained with small deviations from the real values showed that this method can be applied in a real-time production line.
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基于图像处理的金属型材截面尺寸识别
在钢铁厂中,对生产系统特性的估计对于调整系统参数以获得最佳效率至关重要。虽然系统参数可以调得很好,但由于生产线中涉及的机器和人为因素,产品可能会出现一些缺陷。尽早发现这些问题很重要。表面缺陷和尺寸偏差是最重要的质量问题。在这项研究中,它的目的是开发一种方法来测量金属型材的尺寸,获得他们的图像。这在检测尺寸偏差时是有用的。介绍了一个模拟实时环境的平台,并使用4个激光光源从金属轮廓上获取图像。材料的形状是由不同相机拍摄的图像组合而成的。通过对图像进行图像处理和数学转换运算,得到实数尺寸。结果表明,该方法与实际值偏差较小,可用于实时生产线。
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